S2S4E to present new forecasting tool for clean energy at E-World

S2S4E will present its new long-term forecasting tool for renewable energy at E-World Energy & Water in Essen from 11-13 February. Visit our stand to learn more about what we are doing to make forecasts for the weeks and months ahead more reliable!

At our stand, which will be part of the Montel stand in hall 3, you will meet Llorenç Lledó from the Barcelona Supercomputing Center, and Karla Hernández and Joan Miquel Anglès from Nnergix Energy Management.

On 11 February at 15:00, Lledó will also present the project and its new forecasting tool – the S2S4E Decision Support Tool – at the E-World Trading and Finance Forum in Hall 1.

The S2S4E Decision Support Tool has been specifically developed for the energy sector. It shows the global climate outlook, with prognosis for precipitation, solar radiation, temperature, wind speed and power demand ranging from one week to three months ahead.

The S2S4E Decision Support Tool is available in a beta version at www.s2s4e.eu/dst and is free to use at least until the end of November 2020.

The tool has been developed by climate scientists in cooperation with energy companies ENBW, EDPR and EDF. It relies on the operational global prognosis from the European Centre for Medium-Range Weather Forecasts, and on forecasts from the National Centers for Environmental Prediction, and statistical methods have been used to calibrate and improve these outlooks.

S2S4E (Sub-Seasonal to Seasonal Climate Forecasting for Energy) is a project funded by the EU’s research and innovation programme Horizon 2020. It is coordinated by the Barcelona Supercomputing Center and the 12 partners in the project come from seven different countries in Europe (Spain, France, Norway, Germany, Italy, United Kingdom and Sweden).

For more information:

11-13 February: Meet us at the Montel stand, hall 3, where we will demonstrate our new forecasting tool.

11 February at 15:00: Presentation by Llorenç Lledó in hall 1, as part of the session entitled “From Futuristic to Normal: AI and Climate Predictions for Forecasting and Trading”.